Various techniques have been developed to detect and locate underground utilities and other manmade or natural subsurface structures. It is well understood that before trenching, boring, or otherwise engaging in invasive subsurface activity to install or access utilities, it is imperative to know the location of any existing utilities and/or obstructions in order to assist in trenching or boring operations and minimize safety risks. Currently, utilities that are installed or otherwise discovered during installation may have their corresponding physical locations manually recorded in order to facilitate future installations. However, such recordation is not particularly reliable, as only a certain percentage of the utilities are recorded, and those that are recorded may have suspect or imprecise location data. As such, currently-existing location data for buried utilities is often incomplete and suspect in terms of accuracy.
One known utility detection technique involves the use of ground penetrating radar (GPR). GPR, in general, is a very good sensor for utility detection purposes, in that GPR is easy to use and provides excellent resolution. However, GPR has problems detecting utilities in certain soil types and conditions that limit GPR's use in many areas of the United States and the world, such as much of southwest United States (e.g., Arizona). GPR data is typically difficult to interpret, and is typically analyzed by highly skilled users.
Use of GPR and other sensors has been proposed, particularly in regions where GPR's use is limited. Although use of other sensors in combination with GPR can yield meaningful subsurface information, such multi-sensor systems produce massive data sets. For example, scanning a 30 foot×50 mile right of way with multiple sensors can generate about one-quarter of a terabyte of raw data. Moreover, multi-sensor system data must be properly analyzed in the context of position data in order to fully and accurately evaluate a given region of the subsurface. Those skilled in the art readily appreciate the complexity and time commitment associated with properly integrating data from multiple sensors with position data when evaluating a given subsurface using a multi-sensor system.